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Measuring the Effects of Non-Identical Data Distribution for Federated
  Visual Classification

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

13 September 2019
T. Hsu
Qi
Matthew Brown
    FedML
ArXivPDFHTML

Papers citing "Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification"

50 / 209 papers shown
Title
Speeding up Heterogeneous Federated Learning with Sequentially Trained
  Superclients
Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients
Riccardo Zaccone
Andrea Rizzardi
Debora Caldarola
Marco Ciccone
Barbara Caputo
FedML
54
14
0
26 Jan 2022
Federated Learning with Heterogeneous Architectures using Graph
  HyperNetworks
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Or Litany
Haggai Maron
David Acuna
Jan Kautz
Gal Chechik
Sanja Fidler
FedML
38
24
0
20 Jan 2022
Towards Federated Learning on Time-Evolving Heterogeneous Data
Towards Federated Learning on Time-Evolving Heterogeneous Data
Yongxin Guo
Tao R. Lin
Xiaoying Tang
FedML
19
30
0
25 Dec 2021
Improving Performance of Federated Learning based Medical Image Analysis
  in Non-IID Settings using Image Augmentation
Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image Augmentation
Alper Cetinkaya
M. Akin
Ş. Sağiroğlu
OOD
FedML
14
16
0
12 Dec 2021
Communication and Energy Efficient Slimmable Federated Learning via
  Superposition Coding and Successive Decoding
Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
Hankyul Baek
Won Joon Yun
Soyi Jung
Jihong Park
Mingyue Ji
Joongheon Kim
M. Bennis
46
1
0
05 Dec 2021
Joint Superposition Coding and Training for Federated Learning over
  Multi-Width Neural Networks
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
Hankyul Baek
Won Joon Yun
Yunseok Kwak
Soyi Jung
Mingyue Ji
M. Bennis
Jihong Park
Joongheon Kim
FedML
71
21
0
05 Dec 2021
Compare Where It Matters: Using Layer-Wise Regularization To Improve
  Federated Learning on Heterogeneous Data
Compare Where It Matters: Using Layer-Wise Regularization To Improve Federated Learning on Heterogeneous Data
Ha Min Son
M. Kim
T. Chung
FedML
14
9
0
01 Dec 2021
Efficient Federated Learning for AIoT Applications Using Knowledge
  Distillation
Efficient Federated Learning for AIoT Applications Using Knowledge Distillation
Tian Liu
Xian Wei
Jun Xia
Xin Fu
Ting Wang
Mingsong Chen
6
15
0
29 Nov 2021
Differentially Private Federated Learning on Heterogeneous Data
Differentially Private Federated Learning on Heterogeneous Data
Maxence Noble
A. Bellet
Aymeric Dieuleveut
FedML
11
102
0
17 Nov 2021
On-Demand Unlabeled Personalized Federated Learning
On-Demand Unlabeled Personalized Federated Learning
Ohad Amosy
G. Eyal
Gal Chechik
FedML
36
2
0
16 Nov 2021
What Do We Mean by Generalization in Federated Learning?
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan
Warren Morningstar
Lin Ning
K. Singhal
OOD
FedML
41
71
0
27 Oct 2021
Federated Learning via Plurality Vote
Federated Learning via Plurality Vote
Kai Yue
Richeng Jin
Chau-Wai Wong
H. Dai
FedML
24
8
0
06 Oct 2021
Efficient and Private Federated Learning with Partially Trainable
  Networks
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed
Zheng Xu
Ankush Garg
Yuan Cao
Mingqing Chen
FedML
49
13
0
06 Oct 2021
SSFL: Tackling Label Deficiency in Federated Learning via Personalized
  Self-Supervision
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision
Chaoyang He
Zhengyu Yang
Erum Mushtaq
Sunwoo Lee
Mahdi Soltanolkotabi
A. Avestimehr
FedML
98
36
0
06 Oct 2021
FairFed: Enabling Group Fairness in Federated Learning
FairFed: Enabling Group Fairness in Federated Learning
Yahya H. Ezzeldin
Shen Yan
Chaoyang He
Emilio Ferrara
A. Avestimehr
FedML
33
197
0
02 Oct 2021
Personalized Federated Learning for Heterogeneous Clients with Clustered
  Knowledge Transfer
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer
Yae Jee Cho
Jianyu Wang
Tarun Chiruvolu
Gauri Joshi
FedML
35
30
0
16 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning
Connecting Low-Loss Subspace for Personalized Federated Learning
S. Hahn
Minwoo Jeong
Junghye Lee
FedML
24
18
0
16 Sep 2021
Iterated Vector Fields and Conservatism, with Applications to Federated
  Learning
Iterated Vector Fields and Conservatism, with Applications to Federated Learning
Zachary B. Charles
Keith Rush
27
6
0
08 Sep 2021
Towards More Efficient Federated Learning with Better Optimization
  Objects
Towards More Efficient Federated Learning with Better Optimization Objects
Zirui Zhu
Ziyi Ye
FedML
11
0
0
19 Aug 2021
Federated Multi-Target Domain Adaptation
Federated Multi-Target Domain Adaptation
Chun-Han Yao
Boqing Gong
Huayu Chen
Qi
Yukun Zhu
Ming-Hsuan Yang
OOD
FedML
11
63
0
17 Aug 2021
Aggregation Delayed Federated Learning
Aggregation Delayed Federated Learning
Ye Xue
Diego Klabjan
Yuan Luo
FedML
OOD
23
5
0
17 Aug 2021
Communication-Efficient Federated Learning via Predictive Coding
Communication-Efficient Federated Learning via Predictive Coding
Kai Yue
Richeng Jin
Chau-Wai Wong
H. Dai
FedML
25
14
0
02 Aug 2021
Precision-Weighted Federated Learning
Precision-Weighted Federated Learning
Jonatan Reyes
Di-Jorio Lisa
Cécile Low-Kam
Marta Kersten-Oertel
FedML
16
35
0
20 Jul 2021
A Field Guide to Federated Optimization
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
...
Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
187
411
0
14 Jul 2021
Personalized Federated Learning over non-IID Data for Indoor
  Localization
Personalized Federated Learning over non-IID Data for Indoor Localization
Peng Wu
Tales Imbiriba
Junha Park
Sunwoo Kim
Pau Closas
FedML
19
28
0
09 Jul 2021
SplitAVG: A heterogeneity-aware federated deep learning method for
  medical imaging
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging
Miao Zhang
Liangqiong Qu
Praveer Singh
Jayashree Kalpathy-Cramer
D. Rubin
OOD
FedML
21
62
0
06 Jul 2021
On Bridging Generic and Personalized Federated Learning for Image
  Classification
On Bridging Generic and Personalized Federated Learning for Image Classification
Hong-You Chen
Wei-Lun Chao
FedML
22
21
0
02 Jul 2021
Personalized Federated Learning with Gaussian Processes
Personalized Federated Learning with Gaussian Processes
Idan Achituve
Aviv Shamsian
Aviv Navon
Gal Chechik
Ethan Fetaya
FedML
32
98
0
29 Jun 2021
Implicit Gradient Alignment in Distributed and Federated Learning
Implicit Gradient Alignment in Distributed and Federated Learning
Yatin Dandi
Luis Barba
Martin Jaggi
FedML
18
31
0
25 Jun 2021
Behavior Mimics Distribution: Combining Individual and Group Behaviors
  for Federated Learning
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning
Hua Huang
Fanhua Shang
Yuanyuan Liu
Hongying Liu
FedML
19
14
0
23 Jun 2021
FedCM: Federated Learning with Client-level Momentum
FedCM: Federated Learning with Client-level Momentum
Jing Xu
Sen Wang
Liwei Wang
Andrew Chi-Chih Yao
FedML
22
94
0
21 Jun 2021
On Large-Cohort Training for Federated Learning
On Large-Cohort Training for Federated Learning
Zachary B. Charles
Zachary Garrett
Zhouyuan Huo
Sergei Shmulyian
Virginia Smith
FedML
21
113
0
15 Jun 2021
Joint Client Scheduling and Resource Allocation under Channel
  Uncertainty in Federated Learning
Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning
Madhusanka Manimel Wadu
S. Samarakoon
M. Bennis
18
51
0
12 Jun 2021
Federated Learning with Buffered Asynchronous Aggregation
Federated Learning with Buffered Asynchronous Aggregation
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
33
288
0
11 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in
  Federated Learning
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning
Liangqiong Qu
Yuyin Zhou
Paul Pu Liang
Yingda Xia
Feifei Wang
Ehsan Adeli
L. Fei-Fei
D. Rubin
FedML
AI4CE
19
174
0
10 Jun 2021
Multi-VFL: A Vertical Federated Learning System for Multiple Data and
  Label Owners
Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners
Vaikkunth Mugunthan
P. Goyal
Lalana Kagal
FedML
24
9
0
10 Jun 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning
  with Non-IID Data
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
Mi Luo
Fei Chen
Dapeng Hu
Yifan Zhang
Jian Liang
Jiashi Feng
FedML
28
328
0
09 Jun 2021
Fast Federated Learning in the Presence of Arbitrary Device
  Unavailability
Fast Federated Learning in the Presence of Arbitrary Device Unavailability
Xinran Gu
Kaixuan Huang
Jingzhao Zhang
Longbo Huang
FedML
27
95
0
08 Jun 2021
Local Adaptivity in Federated Learning: Convergence and Consistency
Local Adaptivity in Federated Learning: Convergence and Consistency
Jianyu Wang
Zheng Xu
Zachary Garrett
Zachary B. Charles
Luyang Liu
Gauri Joshi
FedML
24
39
0
04 Jun 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu
Junyuan Hong
Jiayu Zhou
FedML
27
627
0
20 May 2021
Decentralized Federated Averaging
Decentralized Federated Averaging
Tao Sun
Dongsheng Li
Bao Wang
FedML
45
207
0
23 Apr 2021
Federated Few-Shot Learning with Adversarial Learning
Federated Few-Shot Learning with Adversarial Learning
Chenyou Fan
Jianwei Huang
FedML
13
29
0
01 Apr 2021
FedCor: Correlation-Based Active Client Selection Strategy for
  Heterogeneous Federated Learning
FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning
Minxue Tang
Xuefei Ning
Yitu Wang
Jingwei Sun
Yu Wang
H. Li
Yiran Chen
FedML
27
80
0
24 Mar 2021
Convergence and Accuracy Trade-Offs in Federated Learning and
  Meta-Learning
Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary B. Charles
Jakub Konecný
FedML
21
62
0
08 Mar 2021
Personalized Federated Learning using Hypernetworks
Personalized Federated Learning using Hypernetworks
Aviv Shamsian
Aviv Navon
Ethan Fetaya
Gal Chechik
FedML
38
324
0
08 Mar 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with
  Secure Aggregation
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation
Peter Kairouz
Ziyu Liu
Thomas Steinke
FedML
32
232
0
12 Feb 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts
Binbin Guo
Yuan Mei
Danyang Xiao
Weigang Wu
Ye Yin
Hongli Chang
MoE
47
22
0
31 Dec 2020
FedADC: Accelerated Federated Learning with Drift Control
FedADC: Accelerated Federated Learning with Drift Control
Emre Ozfatura
Kerem Ozfatura
Deniz Gunduz
FedML
40
37
0
16 Dec 2020
Bandit-based Communication-Efficient Client Selection Strategies for
  Federated Learning
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning
Yae Jee Cho
Samarth Gupta
Gauri Joshi
Osman Yağan
FedML
8
67
0
14 Dec 2020
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